A decision tree is a decision support recursive partitioning structure that uses a tree-like model of decisions and their possible consequences, including...

complexity theory, the decision tree model is the model of computation in which an algorithm can be considered to be a decision tree, i.e. a sequence of...

classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations. Tree models where the target variable...

typically simple decision trees. When a decision tree is the weak learner, the resulting algorithm is called gradient-boosted trees; it usually outperforms...

A decision model in decision theory is the starting point for a decision method within a formal (axiomatic) system. Decision models contain at least one...

learning and search algorithms that reduces the size of decision trees by removing sections of the tree that are non-critical and redundant to classify instances...

machines Random-access machines Turing machines Decision tree model External memory model Functional models include: Abstract rewriting systems Combinatory...

by decision analysts with an intuitive semantic that is easy to understand. It is now adopted widely and becoming an alternative to the decision tree which...

n)} time in the algebraic decision tree model of computation, a model that is more suitable for convex hulls, and in this model convex hulls also require...

take the form of a decision tree Decision tree model#Quantum decision tree, decision tree complexity for a quantum decision tree Equitable cake-cutting#Query...

decision forests is an ensemble learning method for classification, regression and other tasks that works by creating a multitude of decision trees during...

{\displaystyle n} , in a comparison-based model of computation such as a decision tree or algebraic decision tree, is Θ ( n log ⁡ n ) {\displaystyle \Theta...

An incremental decision tree algorithm is an online machine learning algorithm that outputs a decision tree. Many decision tree methods, such as C4.5,...

Markov decision process (MDP), also called a stochastic dynamic program or stochastic control problem, is a model for sequential decision making when outcomes...

classical decision trees. Data can be analyzed to see if a quantum decision tree model fits the data better. Quantum probability provides a new way to explain...

tables. However, in this model all program steps are counted, not just decisions. An upper bound for a decision-tree model was given by Meyer auf der...

the decision tree model of computation, certificate complexity is the minimum number of the n {\displaystyle n} input variables of a decision tree that...

technique for improving the classification accuracy of a decision tree. A decision tree is a model used to make predictions by following a flowchart-like...

In decision tree learning, ID3 (Iterative Dichotomiser 3) is an algorithm invented by Ross Quinlan used to generate a decision tree from a dataset. ID3...

model tree (LMT) is a classification model with an associated supervised training algorithm that combines logistic regression (LR) and decision tree learning...

of computers, we adopt the Decision tree model. Let's rephrase a bit of what our objective is. In the Decision tree model, the lower bound to be shown...

Fast-and-frugal tree or matching heuristic (in the study of decision-making) is a simple graphical structure that categorizes objects by asking one question...

Game tree size (total number of possible games) Decision complexity (number of leaf nodes in the smallest decision tree for initial position) Game-tree complexity...

O(n\log \log n)} time. In even more restricted models of computation, such as the algebraic decision tree, the problem can be solved in the somewhat slower...

Quantization Logistic Model Tree Minimum message length (decision trees, decision graphs, etc.) Nearest Neighbor Algorithm Analogical modeling Probably approximately...

used to generate a decision tree developed by Ross Quinlan. C4.5 is an extension of Quinlan's earlier ID3 algorithm. The decision trees generated by C4.5...

rules, procedures or in similar structures like interactive decision trees and flowcharts. A model-driven DSS emphasizes access to and manipulation of a statistical...

reasoning and decision-making. The term for this concept was coined in 1943 by Kenneth Craik, who suggested that the mind constructs "small-scale models" of reality...

becomes O(m log m). A matching lower bound is known in the algebraic decision tree model of computation. The task of computing the volume of a convex polytope...

A decision cycle is said to occur when an explicitly specified decision model is used to guide a decision and then the outcomes of that decision are...